The sample data you'll need is available from this book's GitHub repository at https://github.com/PacktPublishing/R-Bioinformatics-Cookbook. If you want to use the code examples as they are written, then you will need to make sure that this data is in a sub-directory of whatever your working directory is.
Here are the R packages that you'll need. Most of these will install with install.packages(); others are a little more complicated:
- ape
- Bioconductor
- dada2
- phyloseq
- corrplot
- cowplot
- dplyr
- kmer
- magrittr
- metacoder
- RColorBrewer
- vegan
Bioconductor is huge and has its own installation manager. You can install it with the following code:
if (!requireNamespace("BiocManager"))
install.packages("BiocManager")
BiocManager::install()
Normally, in R, a user will load a library and use the functions directly by name. This is great in interactive sessions but it can cause confusion when many packages are loaded. To clarify which package and function I'm using at a given moment, I will occasionally use the packageName::functionName() convention.
letters[1:5]
This will give us the following output:## a b c d e
Note that the output lines are prefixed with ##.